main.py

import sys
import os

# --- PATH FIX ---
current_dir = os.path.dirname(os.path.abspath(__file__))
sys.path.append(current_dir)
# ----------------

from src.data_loader import load_data
from src.spatial_analysis import run_clustering, plot_clusters
from src.econometrics import run_regression, save_summary
# Import all visualization functions
from src.visuals import (
    plot_top_counties, plot_scenario_comparison, plot_correlation,
    plot_ercot_zones, plot_population_vs_risk, plot_water_share_dist,
    plot_count_vs_load, plot_efficiency_savings
)

def main():
    print("--- STARTING RESEARCH COMPENDIUM GENERATION ---")
    
    # 1. Setup Directories
    fig_dir = os.path.join(current_dir, 'output', 'figures')
    tab_dir = os.path.join(current_dir, 'output', 'tables')
    os.makedirs(fig_dir, exist_ok=True)
    os.makedirs(tab_dir, exist_ok=True)
    
    # 2. Load Data
    print("\n[1/4] Loading Data...")
    csv_path = os.path.join(current_dir, 'data', 'texas_dc_refined_v2.csv')
    df_full, df_baseline = load_data(csv_path)
    
    # 3. Generate Descriptive Figures (1-8)
    print("\n[2/4] Generating Figures 1-8...")
    
    plot_top_counties(df_baseline, os.path.join(fig_dir, 'figure1_top_counties.png'))
    plot_scenario_comparison(df_full, os.path.join(fig_dir, 'figure2_scenarios.png'))
    plot_correlation(df_baseline, os.path.join(fig_dir, 'figure3_correlation.png'))
    plot_ercot_zones(df_baseline, os.path.join(fig_dir, 'figure4_ercot_zones.png'))
    plot_population_vs_risk(df_baseline, os.path.join(fig_dir, 'figure5_pop_risk.png'))
    plot_water_share_dist(df_baseline, os.path.join(fig_dir, 'figure6_water_dist.png'))
    plot_count_vs_load(df_baseline, os.path.join(fig_dir, 'figure7_count_load.png'))
    plot_efficiency_savings(df_full, os.path.join(fig_dir, 'figure8_efficiency_savings.png'))
    
    print(f"   [+] Saved Figures 1-8 to {fig_dir}")

    # 4. Spatial Analysis (Figure 9)
    print("\n[3/4] Running Clustering Model (Figure 9)...")
    df_clusters = run_clustering(df_baseline)
    f9_path = os.path.join(fig_dir, 'figure9_risk_clusters.png')
    plot_clusters(df_clusters, f9_path)
    print(f"   [+] Saved Figure 9 to {f9_path}")
    
    # 5. Econometrics
    print("\n[4/4] Running Econometric Analysis...")
    model = run_regression(df_full)
    save_summary(model, os.path.join(tab_dir, 'regression_results.txt'))
    
    print("\n=======================================")
    print("   COMPLETE. All 9 Figures Generated.  ")
    print("=======================================")

if __name__ == "__main__":
    main()